> They may 10x their profit by serving elderly clients but that is assuming x more elderly clients would want to suddenly come.
Or by cutting the cost.
591 karma · joined March 13, 2019
Or by cutting the cost.
I'm only a beginner in Japanese so I might be wrong, but I don't think that's correct. (Or am I missing a joke?)
バッチリ means "perfect" or "fully prepared" and it's an adverb; 日本人 means "a Japanese person". I can't find anywhere stating this phrase means an illeist.
One way to say that is just 一人称を名前で呼ぶ人, which means "a person who uses their name as their first person pronoun."
But hiring is not evaluating a software engineer in general, rather it's to find a person for a specific role and a specific set of work to be done, a tighter range could mean better estimation.
Programming languages' operators like == are actually ASCII arts for the convenience of the machines, never the humans. It is encoding a concept that is not representable in ASCII, so it has to be encoded by a conventional combination of two characters. When reading your own or others code, you have to do this subtle mental labor of decoding the ASCII art back to the concept.
Programming ligatures, on the other hand, alleviate this burden. They conform the intended meaning of the author. It's not a typographical problem, rather it's a communication problem.
For most ligatures, you can guess the underlying ASCII codes, and if you can't guess, you only need to learn once. In an editor or on a webpage, you can copy the code and paste onto something that doesn't have the ligature font enabled to learn its components.
The idea case is Unicode programming like Agda, but it has its own problems like not easy to type and find out how to type, lacking some operators, hard to read with small font size, etc.
Ligatures are a balanced option between the ASCII art and the Unicode programming. Not hell yes, but neither hell no.
According to Microsoft's documentation[0], the microsoft-edge:// scheme opens the edge browser and navigates to the specified URL.
If what is claimed in the article is implemented, it will provide a way to bypass the default browser setting. The system will launch edge even if you set another browser as your default web browser, bringing the problem of leaking MS account information that comes with the edge.
[0]: https://docs.microsoft.com/en-us/windows/uwp/launch-resume/l...
> Academic achievement (n= 2,020) was obtained from administrative records providing the end-of-grade standardized test scores for reading and math for the 2014–2015 school year.
> School belonging (n= 2,104) was assessed with the six-item Psychological Sense of School Membership23 self-report scale of school membership (e.g., I feel like a real part of my school; People at my school are friendly to me; [0] Not at all true to [5] very true), α= 0.84.
> Conduct problems (n= 2,103) were assessed using the 26-item Problem Behavior Frequency Scale24 of behavioral aggression and violence in the last 30 days (e.g., In the last 30 days, how many times have you …skipped school; stolen something from another student; [0] Never, [1] 1–2 times, [2] 3–5 times, [3] 6–9 times, [4] 10–19 times, and [5] 20+ times). This scale was converted into a count of reported problems (binary for each item rated >1 then summed).
> Psychological distress (n=2,104) was assessed using the six-item Kessler Psychological Distress Scale25 to measure the frequency of participants’ feelings of distress over the past month (e.g., During the past 30 days… about how often did you feel worthless; about how often did feel restless or fidgety? [0] None of the time to [4] all of the time), α= 0.66.
> General physical health (n= 2,097) was assessed with an item from the Add Health General Health and Diet survey26 (i.e., In general, how is your health? [0] Poor to [4] excellent).
I find it not surprising that having a social media account is not statistically related to the results of these measurements. And I suspect for example, being exposed to online sexual contents will also not affect as well. When talking about these things, I tend to be skeptical of behaviorism and feel like a more nuanced methodology should be taken.
Continuing with this analogy and using Kuhn's concepts, maybe it's better to bracket out breakthroughs (paradigm shifts) when talking about everyday productivity (normal science).
And in the paper, from the abstract,
> We demonstrate that the Faithfulness property that is assumed in much causal analysis is robustly violated for a large class of systems...
In preliminaries,
> The Faithfulness assumption is that no conditional correlation among the variables is zero unless it is necessarily so given the Markov property.
So probably a more accurate laymam description would be "not all causations are observable as a statistical correlation relationship".
A person can believe alcohol is not harmful to humans health without consuming alcohol, therefore it's morally acceptable if an alcohol producer does not consume alcohol.
But if they don't consume alcohol because they believe alcohol is harmful, while advertising (explicitly or implicitly by helping the alcohol company) that it is not harmful, then that is dishonesty. Because in this case, the person purposefully acts like they believe something for personal benefits, but actually they don't.
I love how in the README, the syntax highlighter doesn't pick up letters with diacritical marks.
It seems like this effort continues even up to now [0].
[0]: http://www.chinadaily.com.cn/a/202101/04/WS5ff25229a31024ad0...
The two books I read and can recommend are Programming Haskell by Graham Hutton & Get programming with Haskell by Will Kurt.
Another source that helped me a lot is the video series Category Theory by Bartosz Milewski [0]. It requires basically no background on category theory and defines all the concepts along the way. Bartosz also uses Haskell code as examples. You only need to know the syntax up to type class to understand.
As for the awful experience people get from learning Haskell, I think it depends a lot on people's expectations.
Most people only learn one language from school or early career, and then migrate their experience from one language to another. You don't learn the concept of "stack" twice, you only "learn" how to express them with a different syntax. So people can "learn" new languages with significantly lower effort than they learned the first language.
And when they find Haskell or other ML-family functional programming languages, they can't find the corresponding concepts in their known language. This time people actually need to learn new concepts as they learned their first language.
The experience is very similar to learning algorithms or OOP design patterns. And I don't think it's harder to learn Haskell up to the level mentioned by the author than e.g. reading the gang-of-four book.
[0]: https://youtube.com/playlist?list=PLbgaMIhjbmEnaH_LTkxLI7FMa...
The problem I see is that there's an upper limit to the quantity of information even with this higher density. And that's a hard limit on the range of topics that this format can cover.
Furthermore, I don't think this can be solved by simply increase the time limit as well, since people can't maintain the same level of attention for a long period of time. Say the content needs 60s with max density. It usually needs to spread out to 120s with lower density for it to be understood better.
For the informational content I consume on YouTube, in a 10min video, the parts that can be removed are usually 30s of opening and 30s of closing. For the rest, though it has lower density than TikTok, I don't think it's possible to compress that much and the low density is in some sense necessary.
Of course, this is specific to how people use YouTube and TikTok. And though I am unlikely to use TikTok from this experience, I still appreciate your input.
Of course, it takes time to fluently "read out" the words, and in practice, it's much easier if you just know the word and pull the pronunciation from your memory.
For the Common Voice project, there are usually two or three words in a batch of five sentences that I don't know. And there are unfamiliar places and names, since most of the text come from Wikipedia. In such case, I'll take my time to use the spelling to infer the correct pronunciation and practice it several times, until I can put it into the sentence. Then I'll record. And I know it must be correct.
If I am not sure about the meaning of the new word (you can usually guess from etymology or word formation), I look it up in the dictionary and learn a new word.
I wonder what gave you such an impression of Esperanto. My personal experience of Esperanto is quite different.
I started to casually self-learn Esperanto about one year ago as my second foreign language apart from English. After about half a year, I was confident enough to join online Esperanto communities and it gave me a surprisingly much more diverse experience than any community I had encountered on the Internet.
For example, in an online chat group, active users mainly come from US, South America, and Russia. As an person from East Asia, there is little chance for me to get in touch with the latter two groups otherwise. And there are often new users from South America who speak only Spanish and Esperanto.
I myself do not identify as a upper-middle class person, and I don't know enough to assess other Esperanto speakers' class status.
The impression of Esperanto speakers being upper-middle class may come from the fact people learn Esperanto as a hobby. But people not in the upper-middle class can have other hobbies, why is Esperanto different? It doesn't come with the many benefits that people may expect from learning a "practical" language, but it takes significantly less effort. I'd say it's about as hard as learning a new instrument. So it is not that exclusive to only upper-middle class people.
After one year of casual learning, I am now able to contribute to the Common Voice project in Esperanto (175 recordings and 123 validations) and I actually use it as a source of learning material.
And nowadays, you can find all of them in big cities like Beijing or Shanghai.
However, it doesn't cover other cases for other AI mistakes you mentioned, like self-driving.
That being said, this level of deep integration means that the moment you boot the cloud PC, all of the data are potentially very vulnerable on the software level.